Function reference • abess

Overview
`abess-package` `_PACKAGE`	abess: Fast Best Subset Selection
Generalized linear model
`abess(<default>)` `abess(<formula>)`	Adaptive best subset selection (for generalized linear model)
`coef(<abess>)`	Extract Model Coefficients from a fitted "`abess`" object.
`deviance(<abess>)`	Extract the deviance from a fitted "`abess`" object.
`extract()`	Extract one model from a fitted "`abess`" object.
`plot(<abess>)`	Creat plot from a fitted "`abess`" object
`predict(<abess>)`	Make predictions from a fitted "`abess`" object.
`print(<abess>)`	Print method for a fitted "`abess`" object
Principal component analysis
`abesspca()`	Adaptive best subset selection for principal component analysis
`coef(<abesspca>)`	Extract Sparse Loadings from a fitted "`abesspca`" object.
`plot(<abesspca>)`	Creat plot from a fitted "`abess`" object
`print(<abesspca>)`	Print method for a fitted "`abesspca`" object
Robust principal component analysis
`abessrpca()`	Adaptive best subset selection for robust principal component analysis
`coef(<abessrpca>)`	Extract sparse component from a fitted "`abessrpca`" object.
`plot(<abessrpca>)`	Creat plot from a fitted "`abessrpca`" object
`print(<abessrpca>)`	Print method for a fitted "`abessrpca`" object
Synthetic datasets
`generate.data()`	Generate simulated data
`generate.matrix()`	Generate matrix composed of a sparse matrix and low-rank matrix
`generate.spc.matrix()`	Generate matrix with sparse principal component
Real-world dataset
`trim32`	The Bardet-Biedl syndrome Gene expression data

Reference